Adaptive variational mode decomposition and its application to multi-fault detection using mechanical vibration
Xiuzhi He1, Xiaoqin Zhou2, Wennian Yu3
1School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130025, PR China; Department of Mechanical and Materials Engineering, Queen's University, Kingston K7L 3N6, Canada.
This study introduces an adaptive variational mode decomposition (AVMD) method for diagnosing multiple faults in rotating machinery. The novel syncretic impact index (SII) and artificial bee colony (ABC) algorithm effectively optimize parameters, improving fault separation.
Area of Science:
- Mechanical Engineering
- Signal Processing
- Condition Monitoring
Background:
- Diagnosing multiple transient faults in rotating machinery using vibration signals is complex.
- Variational Mode Decomposition (VMD) shows promise for fault decoupling but requires predefined parameters, leading to suboptimal performance.
- Existing adaptive VMD methods suffer from issues like mode redundancy and sensitivity to random impacts.
Purpose of the Study:
- To develop an improved adaptive variational mode decomposition (AVMD) method for enhanced rotating machinery fault diagnosis.
- To introduce a novel syncretic impact index (SII) for accurate evaluation of impulsive fault components.
- To optimize VMD parameters using the artificial bee colony (ABC) algorithm for superior fault signal separation.
Main Methods:
- Developed an adaptive variational mode decomposition (AVMD) method.
- Introduced a novel syncretic impact index (SII) to effectively isolate fault impacts and mitigate interference.
- Utilized the artificial bee colony (ABC) algorithm to determine optimal VMD parameters based on the SII.
- Employed the envelope power spectrum for robust fault feature extraction.
Main Results:
- The proposed AVMD method, utilizing SII and ABC, demonstrated superior performance in separating impulsive multi-fault signals.
- Simulated signal analysis and experimental applications confirmed the effectiveness of the AVMD method.
- The method successfully overcame limitations of traditional VMD and existing adaptive techniques, such as mode redundancy.
Conclusions:
- The developed AVMD method provides an efficient and effective approach for multi-fault diagnosis in rotating machinery.
- The syncretic impact index (SII) is a valuable tool for identifying critical fault components in complex vibration signals.
- Optimizing VMD parameters via the ABC algorithm significantly enhances diagnostic accuracy for multiple transient faults.
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